Solving complex optimization models is NP-hard, meaning the solution time increases exponentially in the worst case. This, together with other challenges such as uncertainty and nonlinearity, result in many real-world optimization models not being solvable in reasonable time. Using alternative formulations and solution approaches could speed up the solution process, but finding alternative approaches is still a manual process requiring deep optimization expertise.
Currently, there is no system or methods available to automatically generate alternative approaches through built-in expert knowledge.